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Record W2787477639 · doi:10.1080/13607863.2018.1428935

Differences in neuropsychiatric symptoms between nursing home residents with young-onset dementia and late-onset dementia

2018· article· en· W2787477639 on OpenAlexfundno aff
Britt Appelhof, Christian Bakker, Jeannette C.L. van Duinen‐van den IJssel, Sandra A. Zwijsen, Martin Smalbrugge, Frans R.J. Verhey, Marjolein de Vugt, Sytse U. Zuidema, Raymond T.C.M. Koopmans

Bibliographic record

VenueAging & Mental Health · 2018
Typearticle
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsnot available
FundersZonMwAlzheimer Society
KeywordsApathyDementiaPsychological interventionMedicinePsychiatryNursing homesPsychologyClinical psychologyPediatricsCognitionDiseaseInternal medicineNursing

Abstract

fetched live from OpenAlex

OBJECTIVE: The aims of the current study are (1) to explore the differences in neuropsychiatric symptoms (NPS) between young-onset dementia (YOD) and late-onset dementia (LOD), and (2) to investigate whether the possible differences can be attributed to differences in dementia subtype, gender, psychotropic drug use (PDU), or dementia severity. METHOD: Three hundred and eighty-six nursing home (NH) residents with YOD and 350 with LOD were included. Multilevel modeling was used to compare NPS between the groups . Furthermore, dementia subtype, gender, PDU, and dementia severity were added to the crude multilevel models to investigate whether the possible differences in NPS could be attributed to these characteristics. RESULTS: Higher levels of apathy were found in NH residents with YOD. After the characteristics were added to the models, also lower levels of verbally agitated behaviors were found in YOD . CONCLUSION: We recommend that special attention be paid to interventions targeting apathy in YOD. Although no differences in other NPS were found, the PDU rates were higher in YOD, suggesting that the threshold for the use of PDU in the management of NPS is lower. This underscores the need for appropriate attention to non-pharmacological interventions for the management of NPS in YOD.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.924

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.017
GPT teacher head0.332
Teacher spread0.315 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations14
Published2018
Admission routes1
Has abstractyes

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